Life Prediction Model of Wooden Structure Based on Artificial Intelligence Algorithm
The ancient wooden structure in China is a precious architectural cultural heritage in history, which has high cultural and artistic value. However, due to the influence of its own material structure and the long-term preservation and maintenance process, due to long-term loads, earthquakes, fires,...
Gespeichert in:
Veröffentlicht in: | Mobile information systems 2022-05, Vol.2022, p.1-10 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 10 |
---|---|
container_issue | |
container_start_page | 1 |
container_title | Mobile information systems |
container_volume | 2022 |
creator | Cao, Ningning |
description | The ancient wooden structure in China is a precious architectural cultural heritage in history, which has high cultural and artistic value. However, due to the influence of its own material structure and the long-term preservation and maintenance process, due to long-term loads, earthquakes, fires, man-made damage, etc., ancient buildings have suffered more or less damage, which may cause sudden failure of the structure, which seriously affects the safety of the building structure. Therefore, the research on the prediction of the life of ancient wooden structures has guiding significance for sustainable development. This paper studies the life prediction of ancient buildings and introduces artificial intelligence algorithms. By comparing the old and new of the ancient building with the damage of the various structures of the ancient building, and using a variety of methods to find a more accurate method to predict the life of the ancient building, through various aspects of research and comparison, we have discovered the variation of wooden columns and beams. The coefficients are 22.97% and 22.54%, which affect the service life of wooden members. The residual strength ratios of the compressive design strength and flexural design strength of the new material and the old material are 60.42% and 26.67%, respectively. |
doi_str_mv | 10.1155/2022/3591967 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2675430195</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2675430195</sourcerecordid><originalsourceid>FETCH-LOGICAL-c267t-d045a6cc3340710a66168580f9439d6d8c4d6a1388467b4c3aa015b3308054113</originalsourceid><addsrcrecordid>eNp90EtLAzEUBeAgCtbqzh8QcKljbyavmWUtPgoVBSt2N6RJpk2ZTmqSQfz3TmnXru5ZfNwDB6FrAveEcD7KIc9HlJekFPIEDUgheVYCX5z2mUuWAZGLc3QR4wZAAOVygOYzV1v8HqxxOjnf4ldvbIN9jb98n1r8kUKnUxcsflDRGtyTcUiudtqpBk_bZJvGrWyrLR43Kx9cWm8v0VmtmmivjneIPp8e55OXbPb2PJ2MZ5nOhUyZAcaV0JpSBpKAEoKIghdQl4yWRphCMyMUoUXBhFwyTZUCwpeUQgGcEUKH6Obwdxf8d2djqja-C21fWfUFnFEgJe_V3UHp4GMMtq52wW1V-K0IVPvdqv1u1XG3nt8e-Nq1Rv24__Ufya1q3w</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2675430195</pqid></control><display><type>article</type><title>Life Prediction Model of Wooden Structure Based on Artificial Intelligence Algorithm</title><source>Wiley Online Library Open Access</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><creator>Cao, Ningning</creator><contributor>Zhu, Fusheng</contributor><creatorcontrib>Cao, Ningning ; Zhu, Fusheng</creatorcontrib><description>The ancient wooden structure in China is a precious architectural cultural heritage in history, which has high cultural and artistic value. However, due to the influence of its own material structure and the long-term preservation and maintenance process, due to long-term loads, earthquakes, fires, man-made damage, etc., ancient buildings have suffered more or less damage, which may cause sudden failure of the structure, which seriously affects the safety of the building structure. Therefore, the research on the prediction of the life of ancient wooden structures has guiding significance for sustainable development. This paper studies the life prediction of ancient buildings and introduces artificial intelligence algorithms. By comparing the old and new of the ancient building with the damage of the various structures of the ancient building, and using a variety of methods to find a more accurate method to predict the life of the ancient building, through various aspects of research and comparison, we have discovered the variation of wooden columns and beams. The coefficients are 22.97% and 22.54%, which affect the service life of wooden members. The residual strength ratios of the compressive design strength and flexural design strength of the new material and the old material are 60.42% and 26.67%, respectively.</description><identifier>ISSN: 1574-017X</identifier><identifier>EISSN: 1875-905X</identifier><identifier>DOI: 10.1155/2022/3591967</identifier><language>eng</language><publisher>Amsterdam: Hindawi</publisher><subject>Algorithms ; Architecture ; Artificial intelligence ; Buildings ; Coefficient of variation ; Columns (structural) ; Compressive strength ; Cultural heritage ; Cultural resources ; Culture ; Earthquake damage ; Fire damage ; Historical buildings ; Historical structures ; Life prediction ; Methods ; Neural networks ; Optimization ; Prediction models ; Radiation ; Residual strength ; Service life ; Sustainable development ; Values ; Wooden structures</subject><ispartof>Mobile information systems, 2022-05, Vol.2022, p.1-10</ispartof><rights>Copyright © 2022 Ningning Cao.</rights><rights>Copyright © 2022 Ningning Cao. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c267t-d045a6cc3340710a66168580f9439d6d8c4d6a1388467b4c3aa015b3308054113</citedby><cites>FETCH-LOGICAL-c267t-d045a6cc3340710a66168580f9439d6d8c4d6a1388467b4c3aa015b3308054113</cites><orcidid>0000-0001-5874-123X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><contributor>Zhu, Fusheng</contributor><creatorcontrib>Cao, Ningning</creatorcontrib><title>Life Prediction Model of Wooden Structure Based on Artificial Intelligence Algorithm</title><title>Mobile information systems</title><description>The ancient wooden structure in China is a precious architectural cultural heritage in history, which has high cultural and artistic value. However, due to the influence of its own material structure and the long-term preservation and maintenance process, due to long-term loads, earthquakes, fires, man-made damage, etc., ancient buildings have suffered more or less damage, which may cause sudden failure of the structure, which seriously affects the safety of the building structure. Therefore, the research on the prediction of the life of ancient wooden structures has guiding significance for sustainable development. This paper studies the life prediction of ancient buildings and introduces artificial intelligence algorithms. By comparing the old and new of the ancient building with the damage of the various structures of the ancient building, and using a variety of methods to find a more accurate method to predict the life of the ancient building, through various aspects of research and comparison, we have discovered the variation of wooden columns and beams. The coefficients are 22.97% and 22.54%, which affect the service life of wooden members. The residual strength ratios of the compressive design strength and flexural design strength of the new material and the old material are 60.42% and 26.67%, respectively.</description><subject>Algorithms</subject><subject>Architecture</subject><subject>Artificial intelligence</subject><subject>Buildings</subject><subject>Coefficient of variation</subject><subject>Columns (structural)</subject><subject>Compressive strength</subject><subject>Cultural heritage</subject><subject>Cultural resources</subject><subject>Culture</subject><subject>Earthquake damage</subject><subject>Fire damage</subject><subject>Historical buildings</subject><subject>Historical structures</subject><subject>Life prediction</subject><subject>Methods</subject><subject>Neural networks</subject><subject>Optimization</subject><subject>Prediction models</subject><subject>Radiation</subject><subject>Residual strength</subject><subject>Service life</subject><subject>Sustainable development</subject><subject>Values</subject><subject>Wooden structures</subject><issn>1574-017X</issn><issn>1875-905X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><recordid>eNp90EtLAzEUBeAgCtbqzh8QcKljbyavmWUtPgoVBSt2N6RJpk2ZTmqSQfz3TmnXru5ZfNwDB6FrAveEcD7KIc9HlJekFPIEDUgheVYCX5z2mUuWAZGLc3QR4wZAAOVygOYzV1v8HqxxOjnf4ldvbIN9jb98n1r8kUKnUxcsflDRGtyTcUiudtqpBk_bZJvGrWyrLR43Kx9cWm8v0VmtmmivjneIPp8e55OXbPb2PJ2MZ5nOhUyZAcaV0JpSBpKAEoKIghdQl4yWRphCMyMUoUXBhFwyTZUCwpeUQgGcEUKH6Obwdxf8d2djqja-C21fWfUFnFEgJe_V3UHp4GMMtq52wW1V-K0IVPvdqv1u1XG3nt8e-Nq1Rv24__Ufya1q3w</recordid><startdate>20220531</startdate><enddate>20220531</enddate><creator>Cao, Ningning</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-5874-123X</orcidid></search><sort><creationdate>20220531</creationdate><title>Life Prediction Model of Wooden Structure Based on Artificial Intelligence Algorithm</title><author>Cao, Ningning</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c267t-d045a6cc3340710a66168580f9439d6d8c4d6a1388467b4c3aa015b3308054113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Architecture</topic><topic>Artificial intelligence</topic><topic>Buildings</topic><topic>Coefficient of variation</topic><topic>Columns (structural)</topic><topic>Compressive strength</topic><topic>Cultural heritage</topic><topic>Cultural resources</topic><topic>Culture</topic><topic>Earthquake damage</topic><topic>Fire damage</topic><topic>Historical buildings</topic><topic>Historical structures</topic><topic>Life prediction</topic><topic>Methods</topic><topic>Neural networks</topic><topic>Optimization</topic><topic>Prediction models</topic><topic>Radiation</topic><topic>Residual strength</topic><topic>Service life</topic><topic>Sustainable development</topic><topic>Values</topic><topic>Wooden structures</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Ningning</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Mobile information systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Ningning</au><au>Zhu, Fusheng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Life Prediction Model of Wooden Structure Based on Artificial Intelligence Algorithm</atitle><jtitle>Mobile information systems</jtitle><date>2022-05-31</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>10</epage><pages>1-10</pages><issn>1574-017X</issn><eissn>1875-905X</eissn><abstract>The ancient wooden structure in China is a precious architectural cultural heritage in history, which has high cultural and artistic value. However, due to the influence of its own material structure and the long-term preservation and maintenance process, due to long-term loads, earthquakes, fires, man-made damage, etc., ancient buildings have suffered more or less damage, which may cause sudden failure of the structure, which seriously affects the safety of the building structure. Therefore, the research on the prediction of the life of ancient wooden structures has guiding significance for sustainable development. This paper studies the life prediction of ancient buildings and introduces artificial intelligence algorithms. By comparing the old and new of the ancient building with the damage of the various structures of the ancient building, and using a variety of methods to find a more accurate method to predict the life of the ancient building, through various aspects of research and comparison, we have discovered the variation of wooden columns and beams. The coefficients are 22.97% and 22.54%, which affect the service life of wooden members. The residual strength ratios of the compressive design strength and flexural design strength of the new material and the old material are 60.42% and 26.67%, respectively.</abstract><cop>Amsterdam</cop><pub>Hindawi</pub><doi>10.1155/2022/3591967</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-5874-123X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1574-017X |
ispartof | Mobile information systems, 2022-05, Vol.2022, p.1-10 |
issn | 1574-017X 1875-905X |
language | eng |
recordid | cdi_proquest_journals_2675430195 |
source | Wiley Online Library Open Access; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection |
subjects | Algorithms Architecture Artificial intelligence Buildings Coefficient of variation Columns (structural) Compressive strength Cultural heritage Cultural resources Culture Earthquake damage Fire damage Historical buildings Historical structures Life prediction Methods Neural networks Optimization Prediction models Radiation Residual strength Service life Sustainable development Values Wooden structures |
title | Life Prediction Model of Wooden Structure Based on Artificial Intelligence Algorithm |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-13T06%3A18%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Life%20Prediction%20Model%20of%20Wooden%20Structure%20Based%20on%20Artificial%20Intelligence%20Algorithm&rft.jtitle=Mobile%20information%20systems&rft.au=Cao,%20Ningning&rft.date=2022-05-31&rft.volume=2022&rft.spage=1&rft.epage=10&rft.pages=1-10&rft.issn=1574-017X&rft.eissn=1875-905X&rft_id=info:doi/10.1155/2022/3591967&rft_dat=%3Cproquest_cross%3E2675430195%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2675430195&rft_id=info:pmid/&rfr_iscdi=true |